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@ARTICLE{Zaimenko:143600,
      author       = {I. Zaimenko and C. Jaeger and H. Brenner$^*$ and J.
                      Chang-Claude$^*$ and M. Hoffmeister$^*$ and C.
                      Grötzinger$^*$ and K. Detjen and S. Burock and C. A.
                      Schmitt$^*$ and U. Stein$^*$ and J. Lisec},
      title        = {{N}on-invasive metastasis prognosis from plasma metabolites
                      in stage {II} colorectal cancer patients: {T}he {DACHS}
                      study.},
      journal      = {International journal of cancer},
      volume       = {145},
      number       = {1},
      issn         = {1097-0215},
      address      = {Bognor Regis},
      publisher    = {Wiley-Liss},
      reportid     = {DKFZ-2019-01180},
      pages        = {221 - 231},
      year         = {2019},
      abstract     = {Metastasis is the main cause of death from colorectal
                      cancer (CRC). About $20\%$ of stage II CRC patients develop
                      metastasis during the course of disease. We performed
                      metabolic profiling of plasma samples from non-metastasized
                      and metachronously metastasized stage II CRC patients to
                      assess the potential of plasma metabolites to serve as
                      biomarkers for stratification of stage II CRC patients
                      according to metastasis risk. We compared the metabolic
                      profiles of plasma samples prospectively obtained prior to
                      metastasis formation from non-metastasized vs.
                      metachronously metastasized stage II CRC patients of the
                      German population-based case-control multicenter DACHS study
                      retrospectively. Plasma samples were analyzed from stage II
                      CRC patients for whom follow-up data including the
                      information on metachronous metastasis were available. To
                      identify metabolites distinguishing non-metastasized from
                      metachronously metastasized stage II CRC patients robust
                      supervised classifications using decision trees and support
                      vector machines were performed and verified by 10-fold
                      cross-validation, by nested cross-validation and by
                      traditional validation using training and test sets. We
                      found that metabolic profiles distinguish non-metastasized
                      from metachronously metastasized stage II CRC patients.
                      Classification models from decision trees and support vector
                      machines with 10-fold cross-validation gave average accuracy
                      of 0.75 (sensitivity 0.79, specificity 0.7) and 0.82
                      (sensitivity 0.85, specificity 0.77), respectively,
                      correctly predicting metachronous metastasis in stage II CRC
                      patients. Taken together, plasma metabolic profiles
                      distinguished non-metastasized and metachronously
                      metastasized stage II CRC patients. The classification
                      models consisting of few metabolites stratify non-invasively
                      stage II CRC patients according to their risk for
                      metachronous metastasis.},
      cin          = {C070 / C020 / L201 / L101},
      ddc          = {610},
      cid          = {I:(DE-He78)C070-20160331 / I:(DE-He78)C020-20160331 /
                      I:(DE-He78)L201-20160331 / I:(DE-He78)L101-20160331},
      pnm          = {312 - Functional and structural genomics (POF3-312)},
      pid          = {G:(DE-HGF)POF3-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:30560999},
      doi          = {10.1002/ijc.32076},
      url          = {https://inrepo02.dkfz.de/record/143600},
}